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decreasing hardcoded values 134 decreasing the number of calls to an entity bean 124 deployment descriptor 65 cascading deletes 106 CMP 83 CMR 1 to 1 99 CMR 1 to many 102 datasource 79 for a CMP bean 83 for BMT 169 for CMP primary key generation 90 for message-driven bean 203 one-to-one relationship 99 setting transaction control 166 showing a data source 79 showing environment variable 135 vendor specific 62 weblogic for message-driven bean 204 <deploymentdescriptor > 45, 47, 66, 68 <description> 135 <destination-jndi-name> 215 <destination-type> 204 developing noncreatable, readonly entity beans 107 disabling methods for certain users 235 distributed transactions 193 Durable 72 durable subscriptions 165, 199

Figure 13.1 In pessimistic locking, when a user wants to update the data the underlying records are locked and no other user can perform any operation on the data. It is typically implemented using SELECT ... FOR UPDATE semantics.

increases. Pessimistic locking therefore limits the practical number of concurrent users that the system can support. Optimistic locking By contrast, optimistic locking is a strategy that assumes that concurrency problems will occur rarely, and you should detect and resolve each problem when it happens. The optimistic locking mechanism is more difficult to implement, but is a popular approach to enforce control while allowing full data access concurrency. JPA supports the optimistic locking strategy. Although the ActionBazaar system is a high-transaction system, rarely do concurrency problems happen. In the ActionBazaar system, a Seller (as well as the system administrator) is allowed to update her item. Several Bidders may bid for the same item since they are not allowed to change the item. It is less likely that a Seller and an administrator will be updating the same item at the same time, so an optimistic locking strategy makes sense. Figure 13.2 depicts how optimistic locking works. When a user retrieves an entity for update, a copy of the object is provided and changes are made to the copy. After the user makes some changes to the entity, he is ready to save it. The application now obtains a write lock on the object and checks whether data has been updated since the user obtained it. If there has been no update to the original data, then the user is allowed to commit the copy of the entity to the database. Otherwise, the application should throw an exception. The optimistic locking strategy is typically implemented by adding a column to the database table for the entity, and either storing a version number or a

From an implementation perspective, Spring AOP relies on a proxy framework implemented on top of the JDK and the CGLIB proxies, which allows for a more dynamic AOP Compared to other AOP implementations, it makes some of the Spring AOP support less efficient and less flexible In particular, the distinction between call and execution advice is not clear, and the cflow mechanism is not as flexible as in AspectJ or JBoss-AOP Having to create a lot of proxies is also less efficient than more intrusive implementations such as AspectJ On the other hand, the Spring proxying mechanism, and especially the Spring autoproxying mechanism, gives a way to better integrate AOP in a J2EE environment that includes complex legacy code..

Figure 13.2 How optimistic locking strategy is implemented by a persistence provider. If the locking mode is set to WAIT, the User2 would wait until User1 releases the lock.

EJB 18 2.0 specification 5, 202 2.1 149 2.1 specification 145 See also Enterprise JavaBeans EJB clients, using Timer service 146 EJB Container. getting client credentials 234 EJB credentials 234 EJB equality 23